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336                                     Multidimensional Chromatography

                           sensitivity are the most important requirements, and, as well as the use of a suitable
                           selective detector, multidimensional chromatography has also played an important
                           role.
                             Soil extracts are usually very complex. In water samples, humic and fulvic acids
                           make analysis difficult, especially when polar substances are to be determined.
                           Multidimensional chromatography can also make a significant contribution here to
                           this type of analysis.
                             The use of multidimensional chromatography in environmental analysis has been
                           reviewed in the literature (1–6). Of the multidimensional systems described in pre-
                           vious chapters, GC–GC liquid chromatography LC–LC and LC–GC, whose appli-
                           cations to environmental analysis will be detailed in this chapter, are the ones most
                           often used in environmental analysis.
                             Other multidimensional systems, such as supercritical  fluid chromatography
                           (SFC–GC or LC–SFC), will not be described here because, although some applica-
                           tions to environmental analysis have been described (4, 7–9), they have not been
                           very widely used in this field.


                           13.2  MULTIDIMENSIONAL GAS CHROMATOGRAPHY

                           13.2.1  INTRODUCTION

                           Gas chromatography, because of its high resolution, is widely used in environmental
                           analysis to determine a wide range of pollutants. This technique is applied to both
                           volatile and, after a derivatization step, to nonvolatile analytes. Environmental sam-
                           ples are usually quite complex because of the different pollutants  which may be pre-
                           sent. Multidimensional chromatography (MDGC) or GC–GC coupling would
                           therefore be expected to be widely applied in environmental analysis. Despite its
                           many advantages, however, a major drawback with MDGC is that, in principle,
                           many heart-cuts from the first column should be subjected to a second separation. In
                           other words, the method can become extremely time consuming. One remedy is to
                           combine several heart-cuts and analyse these in one second run. However, the risk of
                           co-elution then markedly increases and this is particularly dangerous when detection
                           with no identification power is used. This is what happens, for example, with chlori-
                           nated analytes, for  which electron-capture detection is the most widely used, due to
                           its high sensitivity (5).
                             In general, capillary gas chromatography provides enough resolution for most
                           determinations in environmental analysis. Multidimensional gas chromatography
                           has been applied to environmental analysis mainly to solve separation problems for
                           complex groups of compounds. Important applications of GC–GC can therefore be
                           found in the analysis of organic micropollutants, where compounds such as poly-
                           chlorinated dibenzodioxins (PCDDs) (10), polychlorinated dibenzofurans (PCDFs)
                           (10) and polychlorinated biphenyls (PCBs) (11–15), on account of their similar
                           properties, present serious separation problems. MDGC has also been used to anal-
                           yse other pollutants  in environmental samples (10, 16, 17).
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